Commonly images represented by a digital signal such as medical images are subjected to image processing during or prior to displaying or hard copy recording.
The conversion of grey value pixels into values suitable for reproduction or displaying may comprise a multi-scale image processing method (also called multi-resolution image processing method) by means of which the contrast of the image is enhanced.
According to such a multi-scale image processing method an image, represented by an array of pixel values, is processed by applying the following steps. First the original image is decomposed into a sequence of detail images at multiple scales and occasionally a residual image. Next, the pixel values of the detail images are modified by applying to these pixel values at least one conversion. Finally, a processed image is computed by applying a reconstruction algorithm to the residual image and the modified detail images.
There are limits for the behavior of the conversion functions. Grey value transitions in the image can be distorted to an extent that the appearance becomes unnatural if the conversion functions are excessively non-linear. The distortions are more pronounced in the vicinity of significant grey level transitions, which may result in overshoots at step edges and loss of homogeneity in regions of low variance facing strong step edges. The risk of creating artifacts becomes more significant for CT images since they have sharper grey level transitions, e.g. at the interface of soft tissue and contrast media. One has to be careful using the multi-scale techniques on CT images.
A multi-scale contrast enhancement algorithm which results in a contrast enhanced image while preserving the shape of the edge transitions has been described in co-pending European patent application 06 125 766.3 filed Dec. 11, 2006.
In one embodiment of this method the contrast of an image that is represented by a digital signal is enhanced by performing the following steps.
The digital signal is decomposed into a multi-scale representation comprising at least two detail images representing detail at multiple scales and approximation images of which the detail images are derived, an approximation image at a scale representing the grey values of said image in which all details at that scale have been omitted.
Next, translation difference images are computed of at least one approximation image.
The values of these translation difference images are non-linearly modified.
Then, an amplification image is computed at least one scale as the ratio of 2 images wherein the first image is computed by combining the modified translation difference images at the same or smaller scale and the second image is created by combining unenhanced translation difference images at the same or smaller scale.
An enhanced multi-scale detail representation is then computed by modifying at least one scale the detail image according to the amplification image at that scale.
Finally an enhanced image representation is computed by applying a reconstruction algorithm to the enhanced multi-scale detail representation.
It is an object of the present invention to further enhance this method.